Agronomy Journal 93:364-370 (2001)
© 2001 American Society of Agronomy
SMALL GRAINS
Response of Winter Wheat to Simulated Stand Reduction
Douglas L. Holena,
Philip L. Brucknerb,
John M. Martinb,
Gregg R. Carlsond,
David M. Wichmanc and
James E. Bergb
a Univ. of Minnesota Ext. Service, 219 West Cavour Ave., Fergus Fall, MN 56537
b Dep. Plant Sciences and Plant Pathology, P.O. Box 173140, Montana State Univ., Bozeman, MT 59717-3140
c Central Agric. Res. Center, HC90-Box 20, Moccasin, MT 59462
d Northern Agric. Res. Center, Star Route 36, Box 43, Havre, MT 59501
Corresponding author (bruckner{at}montana.edu)
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ABSTRACT
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Environmental stresses can reduce winter wheat (Triticum aestivum L.) stands to less than optimum densities, forcing producers to assess yield potential from early season plant densities. Our objectives were to assess changes in yield and associated traits resulting from varying spring plant densities, and to determine if these responses varied by cultivar. Three hard red winter wheat cultivars were grown at seven population densities in seven Montana environments. Plant density levels ranging from 10 to 100% of target stand were achieved for each cultivar by planting 215 seeds m-2 in the fall and replacing winter wheat seed with spring wheat seed in proportion to the desired spring survival for each treatment. Cultivars did not differ in mean spring plant density or grain yield but differed for yield components, test weight, and protein concentration. The response to increasing plant density was generally not cultivar specific, as plant density interactions with cultivar were significant only for kernels spike-1. Grain yield increased, as did spikes m-2 and kernels m-2, while kernel weight and kernels spike-1 decreased with increasing spring plant density. Response to increasing spring plant density varied with environment for all traits, but environment effects and linear and quadratic plant density terms accounted for 95% of the variation in interaction means for all traits except tillers plant-1. Maximum grain yield occurred at 140 plants m-2, and 21.5 plants m-2 produced winter wheat grain yield equal to spring wheat grain yield for the same environments.
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INTRODUCTION
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WINTER WHEAT (Triticum aestivum L.) is an integral component of northern Great Plains agriculture. New cultivars with improved winterhardiness and management practices that include snow management and seeding directly into standing stubble have allowed production of winter wheat to expand into areas where it was not possible without these changes (Bauer and Black, 1990; Cox et al., 1986). Winter wheat has a yield advantage over spring wheat with comparable inputs (Quisenberry and Clark, 1929; Entz and Fowler, 1991). However, producers in the northern Great Plains risk winter wheat stand losses due to harsh environmental conditions between fall dormancy and spring regrowth. Over the past 13 yr, 15% of the seeded winter wheat area in Montana has gone unharvested, primarily due to winterkill (Stringer, 1999). The severity and frequency of stand loss is dependent upon factors such as temperature fluctuation, wind, snow cover and drift patterns, topography, overwintering plant growth stage, plant diseases, and cultivar winterhardiness. Low temperatures combined with lack of snow cover and high winds contribute to plant losses through desiccation, while suffocation occurs due to ice sheeting or encasement. Stand losses occur most commonly on hilltops, windward slopes, and depressions. If the winter wheat stand is damaged or lost, growers often consider replanting with spring wheat, since crop inputs coincide with those for winter wheat.
Annually, producers must make an early season assessment of winter wheat stand damage, and project final yields. Cereal grain yield recovery in reduced stands occurs via yield component compensation. Yield is dependent upon the sequential development of components defined as: (i) number of spikes per unit area (sometimes subdivided into plants per unit area and spikes per plant); (ii) number of grains per spike; and (iii) individual grain weight (Darwinkle, 1978). For maximum grain production to occur, an undisturbed functioning of the crop is necessary throughout all developmental stages. Evans and Wardlaw (1976) explain yield component compensation as the allowance of subsequently occurring components of final grain yield to compensate for restrictions and/or losses during earlier stages of development, or to maximize reproductive growth under favorable conditions late in the plant life cycle. In general, spikes m-2 increases, while kernels spike-1 and kernel weight decrease with increasing plant density, although the compensation patterns can vary greatly with environment (Blue et al., 1990; Joseph et al., 1985; Darwinkle, 1978; Shanahan et al., 1984). However, in situations of reduced plant density due to environmental stresses, compensation is mainly achieved by extensive tillering of surviving plants.
Many experiments have been conducted to examine grain yield and yield component responses to management variables such as planting date and rate, and depth of seeding and row spacing. An over-riding feature of these seed density studies is that yield declines proportionately faster as seeding rates decline from optimum (Tompkins et al., 1991) and may also decline as rates go beyond optimum (Darwinkle, 1978), creating a yield plateau over a wide range of seeding rates. Black and Bauer (1990) noted that spring plant density was an essential component in predicting final winter wheat grain yield. However, limited research exists regarding winter wheat performance with plant stands diminished by environmental factors such as frost, hail, wind, poor emergence, seedling mortality, or winterkill. The first objective of this study was to assess changes in yield and other agronomic traits in response to varying spring plant densities. A second objective was to determine if these responses were similar across three winter wheat cultivars.
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MATERIALS AND METHODS
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Treatments consisted of three hard red winter wheat cultivars, `CDC Kestrel' (Reg. no. 3468), `Judith' (PI 584526), and `Neeley' (CI 17860) in combination with seven plant density levels corresponding to 100, 75, 50, 40, 30, 20, and 10% of the target stand of 215 seeds m-2. CDC Kestrel is rated 5, while both Judith and Neeley are rated 3 for winter survival (Berg et al., 1999), with 5 being best winter survival. The levels were achieved by planting 215 seeds m-2 in the fall and replacing winter wheat seed with `Fortuna' (CI 13596) spring wheat seed in proportion to the desired spring stand for each cultivar. The recommended seeding rate in the northern Great Plains is 108 to 215 seeds m-2 (34–67 kg ha-1) (Berg et al., 1999). This approach was used to simulate natural stand loss by means of entering winter with complete stands and experiencing density reductions throughout winter months. Fortuna spring wheat was selected because of recognizable seedling characteristics as well as being an awnless cultivar, allowing for easy identification of spring wheat survival.
The 21 treatment combinations were arranged in a randomized complete block design with three replications. Plots consisted of six rows 6.1 m long and spaced 0.3 m apart. The experiment was planted at Bozeman, MT, in fall 1993 and 1994 on Amsterdam silt loam soil (fine-silty, mixed Typic Haploboroll); Moccasin, MT, in fall 1994 and 1995 on Judith clay loam soil (fine-loamy, Typic Calciboroll); Havre, MT, in fall 1994 and 1995 on Telstad clay loam soil (fine-loamy, mixed Aridic Argiborolls); and 50 km north of Havre in fall 1994 on Telstad loam soil (fine-loamy, mixed Aridic Argiborolls). Planting occurred between 23 and 30 September. Grain was harvested from 4.9 m of the center four rows from each plot, and harvest occurred between 9 August and 22 September. Straw was applied to the 100% survival treatments and held in place with twine and stakes at Bozeman in 1994 to minimize natural winterkill. Due to seedlings being smothered by the straw, the treatment was lost for this environment. Two sets of 100% survival treatments were included in all succeeding environments. One set had straw held in place with mesh netting and the other was left uncovered. The set with the highest level of survival was used for analysis as the control plant density.
Weeds were controlled with herbicide applications in the spring. Herbicides applied were: bromoxynil (3,5-dibromo-4-hydroxybenzonitrile) + MCPA [(4-chloro-2-methylphenoxy) acetic acid] at Bozeman in 1994 and 1995, bromoxynil at Havre in 1995 and 1996, clopyralid (3,6-dichloro-2-pyridinecarboxylic acid) + 2, 4-D [(2,4-dichlorophenoxy) acedic acid] at Moccasin in 1995, 2, 4-D at Moccasin in 1996, and tribenuron {2-[[[[(4-methoxy-6-methyl-1,3,5-triazin-2-yl)methylamino]carbonyl]amino]sulfonyl]bebzoic acid} + 2, 4-D at North Havre. Because weeds will be more problematic in areas of reduced crop stands, no additional steps were taken to control weeds beyond those outlined to best simulate actual field situations. Plot areas were fertilized in the fall according to soil test recommendations.
Plant densities were recorded shortly after spring regrowth from two 0.91-m sections of row within each plot. Spike density measurements were also taken before harvest from the same areas within each plot. Before harvest, 20 spikes were randomly collected from each plot and processed with a belt thresher, and used to calculate kernels spike-1 and kernel weight. The center four rows of each plot were harvested for grain yield. A subsample of grain was used to determine test weight with a Seedburo (Chicago, IL) test weight scale. Protein concentration was obtained on grain subsamples using an Infratec (Tecator Hoganas, Sweden) whole kernel analyzer.
Grain yields were obtained for the same three winter wheat cultivars from adjacent winter wheat cultivar yield trials in each of the seven environments. Seeding rate was equivalent to our 100% target rate, and field husbandry was the same as in our study. Grain yield from six adapted spring wheat cultivars [`Newana' (CI 17430), `McNeal' (PI 574642), `Amidon' (PI 527682), `Lew' (CI 17429), `Hi-Line' (PI 549275), and `Ernest' (PI 592761)] was also obtained from adjacent spring wheat cultivar yield trials in the same seven environments. The seven environment means from the three trials (winter wheat cultivar trial, spring wheat trial, and 100% target rate from this study) were used to compare the three trial means with t tests.
Data were analyzed via analysis of variance treating cultivars, and plant density treatments as fixed effects, and environments and replications within environments and interactions with environments as random effects in the model using PROC MIXED in SAS (SAS Inst., 1997). Least squares means were obtained for cultivars and the plant density x environment treatment combinations. Significance of interaction variance components was tested using a likelihood ratio test computed as the difference in -2 REML log-likelihood values from models with and without the interaction term included (Littell et al., 1996). The likelihood ratio statistic was tested against a Chi-square statistic with one degree of freedom. Least significant differences to compare main effect cultivar means were computed by multiplying the appropriate t statistic by the computed standard error of the difference between two means. Nature of response to increasing plant density was examined using environment x plant density means and fitting a model including environment, linear and quadratic terms for actual plant survival and interactions of these terms with environment using PROC GLM in SAS (SAS Inst., 1988). Plant density where maximum grain yield occurred was determined by differentiating the quadratic response equation and setting the derivative equal to zero. Correlations were computed between grain yield and other agronomic traits for each environment using the plant density means. Data were logarithmically transformed to linearize the relationships. Homogeneity of correlations over environments was tested with a Chi-square statistic (Steel et al., 1997).
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RESULTS AND DISCUSSION
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Actual spring plant densities were less than target plant densities, and the difference between actual spring survival and target plant density expanded as target density increased (Fig. 1). The percentage of plants surviving at the 100% winter wheat target seeding rate ranged from 58 at Havre in 1996 to 95% for Moccasin in 1995.
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Fig. 1. Surviving spring plant density vs. target winter wheat plant density for seven Montana environments
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Analysis of variance showed differences among plant density treatments for all traits (Table 1). Even though the three cultivars were chosen to represent different levels of winterhardiness, cultivars did not differ in mean spring plant density (Tables 1 and 2). Although cultivars differed significantly for all three yield components, they compensated such that cultivars showed no difference in grain yield. Each cultivar ranked lowest for a different yield component, with Judith lowest for kernels spike-1, CDC Kestrel lowest for kernel weight, and Neeley lowest for spikes m-2 (Table 2). CDC Kestrel also produced the most kernels m-2. Neeley had significantly fewer tillers plant-1 than the other two cultivars. CDC Kestrel was significantly lower in grain protein concentration than the other two (Table 2). There was a 17 kg m-3 difference in test weight between the cultivars with Judith being lowest and Neeley being highest in test weight. The response to increasing plant density was generally not cultivar specific, as interactions of density with cultivars were statistically significant only for kernels spike-1 (Table 1). Johnson et al. (1988) with soft red winter and Andrews et al. (1992) with soft white winter wheat found cultivars reacted similarly over seeding rates for grain yield. However, Tompkins et al. (1991) found optimum seeding rates differed between a semidwarf and standard height hard red winter wheat cultivar. Cultivars showed significant (P < 0.01) interaction with environments for all traits except surviving plants m-2, spikes m-2, and tillers plant-1 (data not shown). The nature of these interactions usually involved expansion of cultivar differences in the high-yield, low-stress environments rather than changes in rank order. Plant density treatments interacted with environments (P < 0.01) for all traits, and the nature of that interaction was investigated further.
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Table 1. Selected F ratios from analysis of variance for three winter wheat cultivars at seven seeding rates and grown in seven environments
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The model incorporating environment, linear, and quadratic spring plant survival terms and interactions accounted for more than 96% of variation in environment x plant density means for all traits (Table 3). On average all traits exhibited a curvilinear response to increasing plant density with both linear and quadratic coefficients being significant. The linear slope interacted with environments for each trait, meaning linear slopes differed depending on the environment. Similarly, the quadratic trend interacted with environments for all traits except grain yield, spikes m-2, and kernels m-2. Therefore, the curvature associated with increasing plant density was environment specific except for grain yield, spikes m-2, and kernels m-2. Although differential response over environments was noted, the relative contribution of interaction terms was small in relation to differences among environments (intercept) and average linear and quadratic response to increasing plant density (Table 3). Inclusion of the interaction terms improved r2 values from 0.86 to 0.96 for tillers plant-1 and from 0.98 to 0.99 for grain yield. Interaction terms accounted for <3% of the variation for the remaining traits.
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Table 3. Selected F values showing relative contribution of environment, surviving spring plant density, and their interaction for explaining variation in agronomic traits for data averaged over three winter wheat cultivars
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Environmental variables were not measured to characterize the environment x plant density interaction, and generally would not be available in winter wheat production situations. Therefore, the average relationship between agronomic traits and surviving plant density shown here would be of most interest and should have general application across northern Great Plains winter wheat environments. Figure 2 depicts the average responses observed for grain yield, while the 95% prediction interval captures variation that would be encountered when predicting future responses. Owing to the curvilinear nature of grain yield response to increasing plant density, largest yield increases occurred at the lowest plant densities with a characteristic plateau across a wide range of plant densities. On average 140 plants m-2 produced maximum grain yield.
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Fig. 2. Average response for regression of winter wheat grain yield on spring plant density with 95% prediction interval
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On average, spikes m-2 and kernels m-2 responded to increasing plant density similar to grain yield with positive linear and negative quadratic slopes (Table 4). On the other hand, kernels spike-1 and kernel weight decreased with increasing plant density displaying negative linear but with positive quadratic slopes. Response for tillers plant-1 took shape similar to kernels spike-1. The decline in kernel weight with increasing plant density indicates conditions were favorable to promote tiller formation and kernels spike-1 and subsequently kernels m-2 but insufficient postanthesis resources prevented kernels from maintaining maximum weight across plant densities. On average grain protein concentration declined, and test weight increased with increasing plant density.
Variation in grain yield created by differing surviving plant densities was positively associated with spikes m-2 and kernels m-2, but negatively associated with kernels spike-1 and tillers plant-1 (Table 5). These associations were consistent over environments. Kernel weight showed greatest disparity in association with grain yield, as it was usually negatively correlated with grain yield, but was positively but not significantly correlated in two environments. Shanahan et al. (1984) also observed kernels m-2 was more consistent in its positive relationship with grain yield than was kernel weight in winter wheat across six environments. Fischer et al. (1977) noted such positive association between grain yield and kernel m-2 was indicative of sink limitations during postanthesis grain filling. Associations of test weight and grain protein concentration with grain yield were also heterogeneous over environments. Where significant associations were observed, test weight was positively correlated with grain yield and grain protein concentration was negatively correlated with grain yield.
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Table 5. Correlations of grain yield with other agronomic traits for seven Montana environments and pooled over environments
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Changes in grain yield and its components as functions of plant density were consistent with previous work, in that a grain yield plateau was maintained over a wide range of plant density because increased spike m-2 outweighed decreased kernels spike-1 and small decreases in kernel weight (Darwinkle, 1978; Joseph et al., 1985; Tompkins et al., 1991; Shanahan et al., 1984). Others have shown that yield and yield component response to seeding rate was mitigated by management factors such as row width (Tompkins et al., 1991; McLeod et al., 1996), planting date (Blue et al., 1990; Andrews et al., 1992; Smid and Jenkinson, 1979), and planting depth (McLeod et al., 1996; Campbell et al., 1991). Plus, specific responses for grain yield and its components to seeding rate were influenced by uncontrolled environmental factors such as precipitation amount and distribution and temperature associated with years and/or location (Blue et al., 1990; Marshal and Ohm, 1987; Tompkins et al., 1991; Johnson et al., 1988).
The effect of varying spring plant densities on agronomic traits is difficult to impose under natural conditions because environmental stresses such as winterkill may not occur differentially within the same environment (Cox et al., 1986). Our study achieved varying spring plant densities within the same environment through natural attrition of fall-planted spring wheat. This study differs from winter wheat seeding rate studies in that differential plant density was not imposed until spring regrowth of surviving winter wheat. Winter wheat stand was also reduced by natural winterkill, and the amount varied with environment. Our methods imposed uniform stands within a given density. This may not simulate actual winter-kill situations, since that often does not occur uniformly over an area. Other studies have related agronomic trait response to seeding rate (Tompkins et al., 1991; Joseph et al., 1985), but actual correspondence to spring plant density was not determined in these studies.
Grain protein concentration and test weight deserve consideration because they are important determinants of economic value for wheat grain. These two traits were opposite in their contribution to economic value, as grain produced from less than recommended plant populations was higher in grain protein concentration but lower in test weight.
Our results have implications for projecting yields from less than optimum winter wheat stands. Fowler et al. (1976) concluded that a surviving stand 65% of an undamaged stand would produce grain yields not significantly lower than the undamaged stand because of yield component compensation. Since tiller initiation occurs between the three-leaf and flag-leaf stages, and that interval is typically shorter for winter wheat in the northern Great Plains than in areas further south, Black and Bauer (1990) concluded that density of surviving plants capable of producing tillers at spring regrowth was critical in predicting final grain yield in the northern Great Plains. They determined about 120 plants m-2 would maximize grain yield compared with 140 plants m-2 determined for our study. The three cultivars selected for this study respond similarly to varying plant densities for grain yield and all other agronomic traits except kernels spike-1. They also did not differ in spring plant survival and responded similarly over environments despite environmental variation for spring plant survival. These results are encouraging in that future predictions would be easier if results could be generalized over cultivars. Cultivars with a wider range in winterhardiness may have reacted differentially to varying spring plant density. The average relationship between winter wheat grain yield and spring plant density should have general utility across northern Great Plains environments, as the nature of that relationship depended very little on environment. The relationship between grain yield and spring plant density would be useful for projecting grain yield when winter wheat stands are uniformly reduced by environmental stresses before spring regrowth. A grower or consultant could use historical yields or expected grain yield based on stored soil water and soil nutrients as maximum grain yield for about 140 plants m-2, and then determine the intercept to use in the equation. Grain yields could then be projected from the spring plant density. The relationship derived here does not take into account that plants remaining following environmental stress that occurs prior to spring regrowth may be less vigorous than those from undamaged stands.
A grower may opt to replant with another crop when winter wheat stands are reduced from environmental factors. Spring wheat is a logical alternative to replace a failed winter wheat stand in the northern Great Plains because inputs coincide closely for the two crops. Mean yield of the three winter wheat cultivars from our study at the 100% of target seeding rate did not differ from the same three cultivars grown in an adjacent yield trial when averaged over the seven environments (4640 kg ha-1 vs. 4670 kg ha-1). Mean yield of six spring wheat cultivars grown in the same seven environments was 3450 kg ha-1 and was significantly (P < 0.01) less than the winter wheat means. This represents a 34% yield advantage for winter wheat. Entz and Fowler (1991) showed a 26 to 36% yield advantage for winter wheat over spring wheat. These figures probably overstate spring wheat compared with winter wheat yield when spring wheat is planted into a failed winter stand, because fall-grown winter wheat would deplete some stored soil moisture. Using the average response equation from Fig. 2, 21.5 plants m-2 for winter wheat would produce grain yield equal to the average spring wheat yield (3450 kg ha-1). This plant density is at the extreme lower end of densities evaluated in our study. A treatment where spring wheat is planted into destroyed winter wheat would need to be included in an experiment such as ours to determine the winter wheat stand density that would produce grain yield equal to spring wheat. Since our data showed 21.5 plants m-2 produced winter wheat grain yield equal to spring wheat grain yield, a grower would be well advised to leave a reduced stand of winter wheat rather than replant to spring wheat, provided more that about 20 plants m-2 remain at spring regrowth, the stand is reasonably uniform, and weeds can be controlled in the reduced stand.
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NOTES
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Contribution from the Montana Agric. Exp. Stn. Journal Series no. 2000-15.
Received for publication January 26, 2000.
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ABSTRACT
INTRODUCTION
